Links to Exploration step
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Accelerating Medical Research using the Swift Workflow System</title><author><name sortKey="Stef Praun, Tiberiu" sort="Stef Praun, Tiberiu" uniqKey="Stef Praun T" first="Tiberiu" last="Stef-Praun">Tiberiu Stef-Praun</name><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Clifford, Benjamin" sort="Clifford, Benjamin" uniqKey="Clifford B" first="Benjamin" last="Clifford">Benjamin Clifford</name><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Foster, Ian" sort="Foster, Ian" uniqKey="Foster I" first="Ian" last="Foster">Ian Foster</name><affiliation><nlm:aff id="A1"> Argonne National Labs</nlm:aff></affiliation><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Hasson, Uri" sort="Hasson, Uri" uniqKey="Hasson U" first="Uri" last="Hasson">Uri Hasson</name><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Hategan, Mihael" sort="Hategan, Mihael" uniqKey="Hategan M" first="Mihael" last="Hategan">Mihael Hategan</name><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Small, Steven L" sort="Small, Steven L" uniqKey="Small S" first="Steven L." last="Small">Steven L. Small</name><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Wilde, Michael" sort="Wilde, Michael" uniqKey="Wilde M" first="Michael" last="Wilde">Michael Wilde</name><affiliation><nlm:aff id="A1"> Argonne National Labs</nlm:aff></affiliation><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Zhao, Yong" sort="Zhao, Yong" uniqKey="Zhao Y" first="Yong" last="Zhao">Yong Zhao</name><affiliation><nlm:aff id="A1"> Argonne National Labs</nlm:aff></affiliation><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">17476063</idno><idno type="pmc">2676238</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2676238</idno><idno type="RBID">PMC:2676238</idno><date when="2007">2007</date><idno type="wicri:Area/Pmc/Corpus">000303</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Accelerating Medical Research using the Swift Workflow System</title><author><name sortKey="Stef Praun, Tiberiu" sort="Stef Praun, Tiberiu" uniqKey="Stef Praun T" first="Tiberiu" last="Stef-Praun">Tiberiu Stef-Praun</name><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Clifford, Benjamin" sort="Clifford, Benjamin" uniqKey="Clifford B" first="Benjamin" last="Clifford">Benjamin Clifford</name><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Foster, Ian" sort="Foster, Ian" uniqKey="Foster I" first="Ian" last="Foster">Ian Foster</name><affiliation><nlm:aff id="A1"> Argonne National Labs</nlm:aff></affiliation><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Hasson, Uri" sort="Hasson, Uri" uniqKey="Hasson U" first="Uri" last="Hasson">Uri Hasson</name><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Hategan, Mihael" sort="Hategan, Mihael" uniqKey="Hategan M" first="Mihael" last="Hategan">Mihael Hategan</name><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Small, Steven L" sort="Small, Steven L" uniqKey="Small S" first="Steven L." last="Small">Steven L. Small</name><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Wilde, Michael" sort="Wilde, Michael" uniqKey="Wilde M" first="Michael" last="Wilde">Michael Wilde</name><affiliation><nlm:aff id="A1"> Argonne National Labs</nlm:aff></affiliation><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author><author><name sortKey="Zhao, Yong" sort="Zhao, Yong" uniqKey="Zhao Y" first="Yong" last="Zhao">Yong Zhao</name><affiliation><nlm:aff id="A1"> Argonne National Labs</nlm:aff></affiliation><affiliation><nlm:aff id="A2"> University of Chicago</nlm:aff></affiliation></author></analytic><series><title level="j">Studies in health technology and informatics</title><idno type="ISSN">0926-9630</idno><imprint><date when="2007">2007</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p id="P1">Both medical research and clinical practice are starting to involve large quantities of data and to require large-scale computation, as a result of the digitization of many areas of medicine. For example, in brain research – the domain that we consider here – a single research study may require the repeated processing, using computationally demanding and complex applications, of thousands of files corresponding to hundreds of functional MRI studies. Execution efficiency demands the use of parallel or distributed computing, but few medical researchers have the time or expertise to write the necessary parallel programs.</p><p id="P2">The Swift system addresses these concerns. A simple scripting language, SwiftScript, provides for the concise high-level specification of workflows that invoke various application programs on potentially large quantities of data. The Swift engine provides for the efficient execution of these workflows on sequential computers, parallel computers, and/or distributed grids that federate the computing resources of many sites. Last but not least, the Swift provenance catalog keeps track of all actions performed, addressing vital bookkeeping functions that so often cause difficulties in large computations.</p><p id="P3">To illustrate the use of Swift for medical research, we describe its use for the analysis of functional MRI data as part of a research project examining the neurological mechanisms of recovery from aphasia after stroke. We show how SwiftScript is used to encode an application workflow, and present performance results that demonstrate our ability to achieve significant speedups on both a local parallel computing cluster and multiple parallel clusters at distributed sites.</p></div></front></TEI><pmc article-type="research-article" xml:lang="EN"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<pmc-dir>properties manuscript</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-journal-id">9214582</journal-id><journal-id journal-id-type="pubmed-jr-id">21248</journal-id><journal-id journal-id-type="nlm-ta">Stud Health Technol Inform</journal-id><journal-title>Studies in health technology and informatics</journal-title><issn pub-type="ppub">0926-9630</issn></journal-meta><article-meta><article-id pub-id-type="pmid">17476063</article-id><article-id pub-id-type="pmc">2676238</article-id><article-id pub-id-type="manuscript">NIHMS102190</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Accelerating Medical Research using the Swift Workflow System</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>STEF-PRAUN</surname><given-names>Tiberiu</given-names></name><xref ref-type="aff" rid="A2">b</xref><xref ref-type="corresp" rid="CR1">1</xref></contrib><contrib contrib-type="author"><name><surname>CLIFFORD</surname><given-names>Benjamin</given-names></name><xref ref-type="aff" rid="A2">b</xref></contrib><contrib contrib-type="author"><name><surname>FOSTER</surname><given-names>Ian</given-names></name><xref ref-type="aff" rid="A1">a</xref><xref ref-type="aff" rid="A2">b</xref></contrib><contrib contrib-type="author"><name><surname>HASSON</surname><given-names>Uri</given-names></name><xref ref-type="aff" rid="A2">b</xref></contrib><contrib contrib-type="author"><name><surname>HATEGAN</surname><given-names>Mihael</given-names></name><xref ref-type="aff" rid="A2">b</xref></contrib><contrib contrib-type="author"><name><surname>SMALL</surname><given-names>Steven L.</given-names></name><xref ref-type="aff" rid="A2">b</xref></contrib><contrib contrib-type="author"><name><surname>WILDE</surname><given-names>Michael</given-names></name><xref ref-type="aff" rid="A1">a</xref><xref ref-type="aff" rid="A2">b</xref></contrib><contrib contrib-type="author"><name><surname>ZHAO</surname><given-names>Yong</given-names></name><xref ref-type="aff" rid="A1">a</xref><xref ref-type="aff" rid="A2">b</xref></contrib></contrib-group><aff id="A1"><label>a</label> Argonne National Labs</aff><aff id="A2"><label>b</label> University of Chicago</aff><author-notes><corresp id="CR1"><label>1</label>Corresponding Author: Tiberiu Stef-Praun, 5640 S. Elllis rm. 405, University of Chicago, 60615, IL, USA</corresp></author-notes><pub-date pub-type="nihms-submitted"><day>17</day><month>3</month><year>2009</year></pub-date><pub-date pub-type="ppub"><year>2007</year></pub-date><pub-date pub-type="pmc-release"><day>2</day><month>5</month><year>2009</year></pub-date><volume>126</volume><fpage>207</fpage><lpage>216</lpage><abstract><p id="P1">Both medical research and clinical practice are starting to involve large quantities of data and to require large-scale computation, as a result of the digitization of many areas of medicine. For example, in brain research – the domain that we consider here – a single research study may require the repeated processing, using computationally demanding and complex applications, of thousands of files corresponding to hundreds of functional MRI studies. Execution efficiency demands the use of parallel or distributed computing, but few medical researchers have the time or expertise to write the necessary parallel programs.</p><p id="P2">The Swift system addresses these concerns. A simple scripting language, SwiftScript, provides for the concise high-level specification of workflows that invoke various application programs on potentially large quantities of data. The Swift engine provides for the efficient execution of these workflows on sequential computers, parallel computers, and/or distributed grids that federate the computing resources of many sites. Last but not least, the Swift provenance catalog keeps track of all actions performed, addressing vital bookkeeping functions that so often cause difficulties in large computations.</p><p id="P3">To illustrate the use of Swift for medical research, we describe its use for the analysis of functional MRI data as part of a research project examining the neurological mechanisms of recovery from aphasia after stroke. We show how SwiftScript is used to encode an application workflow, and present performance results that demonstrate our ability to achieve significant speedups on both a local parallel computing cluster and multiple parallel clusters at distributed sites.</p></abstract><kwd-group><kwd>Brain research</kwd><kwd>Grid Computing</kwd><kwd>Workflows</kwd></kwd-group><contract-num rid="DC1">R21 DC008638-02</contract-num><contract-num rid="DC1">R01 DC007488-03</contract-num><contract-sponsor id="DC1">National Institute on Deafness and Other Communication Disorders : NIDCD</contract-sponsor></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/CyberinfraV1/Data/Pmc/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 0003038 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Pmc/Corpus/biblio.hfd -nk 0003038 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Ticri/CIDE
|area= CyberinfraV1
|flux= Pmc
|étape= Corpus
|type= RBID
|clé=
|texte=
}}
| This area was generated with Dilib version V0.6.25. |  |